Proto-OKN Theme 1: A Knowledge Graph Warehouse for Neighborhood Information

Proto-OKN 主题 1：社区信息知识图仓库

• 批准号: 2333790
• 负责人: Jing Gao
• 金额: $ 150万
• 依托单位: Purdue University
• 依托单位国家: 美国
• 项目类别: Cooperative Agreement
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2333790&HistoricalAwards=false
• 关键词: Proto; OKN; Theme; Knowledge; Graph

This project aims to establish a robust and sustainable data infrastructure to integrate neighborhood-level data to assist and inform various local stakeholders. Drawing on local records, census data and other neighborhood-level data the project will construct a unified database to capture crucial connections among the variety of neighborhood-level information sources. Project outcomes include integrated neighborhood-level data and software for constructing and operating a knowledge graph warehouse. The educational component of the project will integrate outcomes from this project into course content, foster student mentoring, and promote educational innovation with a focus on inclusivity and diversity within the associated STEM programs. Working in partnership with the National Institute of Justice (NIJ) and other expert entities, this project addresses critical issues in unifying disparate data sources at the neighborhood-level, e.g., demographics, land use, local incidents and injuries, proximity to trauma centers, and the like by leveraging advanced data extraction and record linkage methods. The proposed knowledge graph warehouse is designed to organize and maintain pertinent neighborhood-level information, with data transformation achieved through zero-shot extraction techniques and key-phrase generation methods for free text data. The warehouse will support efficient querying and summarization with adaptable techniques for its unique structure, including novel pattern mining methods for trend detection, ensuring sustainability and extensibility with compatibility for other knowledge graphs, and incorporating incremental updates and extensions for new data and entity types. To ensure data accuracy, the project plans to integrate data from various local agencies, provide user feedback mechanisms, and uphold a robust metadata record. In order to mitigate biases and to provide a comprehensive view, the project will continuously update the infrastructure with new data sources, ensuring transparency through accessibility of metadata and recording of data provenance.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目旨在建立一个强大和可持续的数据基础设施，以整合社区一级的数据，以协助和告知各个地方利益相关者。利用当地记录、人口普查数据和其他社区数据，该项目将建立一个统一的数据库，以捕捉各种社区信息来源之间的关键联系。项目成果包括集成的社区级数据和用于构建和操作知识图谱仓库的软件。该项目的教育部分将把该项目的成果整合到课程内容中，促进学生指导，并促进教育创新，重点关注相关STEM项目的包容性和多样性。该项目与美国国家司法研究所（NIJ）和其他专家实体合作，通过利用先进的数据提取和记录链接方法，解决了在社区一级统一不同数据源的关键问题，例如人口统计、土地使用、当地事件和伤害、靠近创伤中心等。提出的知识图谱仓库旨在组织和维护相关的邻域级信息，并通过零采样提取技术和自由文本数据的关键短语生成方法实现数据转换。该仓库将利用其独特结构的适应性技术支持高效的查询和总结，包括用于趋势检测的新颖模式挖掘方法，确保可持续性和可扩展性与其他知识图的兼容性，并结合针对新数据和实体类型的增量更新和扩展。为了确保数据的准确性，该项目计划整合来自各个地方机构的数据，提供用户反馈机制，并维护健全的元数据记录。为了减少偏见并提供全面的视图，该项目将不断使用新的数据源更新基础设施，通过元数据的可访问性和数据来源的记录来确保透明度。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。